Advances in artificial intelligence (AI) continue to reshape digital product development, yet the day-to-day tools for developers and designers remain bound to flat screens and 2D inputs. The intersection of AI and Extended Reality (AI-XR) introduces powerful multimodal interaction channels, such as gaze, motion, or sp...
Current assessments of conversational AI focus mainly on model outputs, including hallucinations and factual errors. These measures matter, but this paper examines risks that may form on the user side during long and repeated interaction. The study follows one user across nearly four thousand conversations with the sam...
There have been numerous attempts to investigate the potential of social robots for education in the field of child-robot interaction (cHRI). However, empirically based models for the integration of robot technologies into aesthetic education in early childhood, especially in music education, are rare. Our approach is...
This systematic mapping review examines 54 gamified interventions aimed at combating misinformation. We analyze the theoretical frameworks, game design, and media contexts of academic and non-academic games. The results indicate a field dominated by web-based simulations and trivia formats. While psychological inoculat...
Omed Abed, Smi Hinterreiter, Sijia Guo et al.· 0 citations
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picoRing dual, an ultra-low-power bimanual interface with a pair of ring-wristbands based on inductive coupling, has the potential to offer ubiquitous finger input for everyday AR interaction.
Hideaki Yamamoto, Yi-Fan Li, Yoshihiro Kawahara et al.· Proceedings of the 2026 ACM...· 0 citations
PAUSE (Patterns of AI Use: Self-Examination), a privacy-by-design web tool that occupies a different niche from these, is described, a lightweight, non-diagnostic reflection aid for private individual use.
It is argued that automation reshapes rather than replaces translation value, creating an interdependent configuration in which technological efficiency enables human communicative work.
Maria Isabel Rivas Ginel, Janiça Hackenbuchner, A. Secara et al.· arXiv.org· 1 citation
CALICO is presented, a human-centered, codebook-aligned annotation workflow that treats prompts as editable, versioned, and optimizable artifacts and integrates codebook parsing, prompt generation, result inspection, prompt versioning, natural language human feedback, and label-supervised prompt optimization through ex...
This position paper draws on AAC as a setting where speech AI failures are most visible and their stakes highest, alongside other underserved speakers - people who stutter, multilingual speakers, and non-binary and transgender users.
Maria Teleki, Kimi Wenzel, Anna Seo Gyeong Choi et al.· 0 citations
Data-to-text driver coaching is often presented as a generic pipeline from telematics events to advice. This paper argues that its content requires localisation because usefulness and credibility depend on drivers'knowledge, prevalent risks, regulation, infrastructure, and available data. Two independently developed sy...
Iniakpokeikiye Peter Thompson, Jawwad Baig, Ehud Reiter et al.· 0 citations
We present a new nonlinear dimensionality reduction method, MAPLE, that enhances UMAP by improving manifold modeling. MAPLE employs a self-supervised learning approach to more efficiently encode low-dimensional manifold geometry. Central to this approach are maximum manifold capacity representations (MMCRs), which help...
Zeyang Huang, Takanori Fujiwara, Angelos Chatzimparmpas et al.· 0 citations
This work presents a robust, multimodal OVR framework fusing user gaze and natural language to identify Points of Interest (POIs), and developed a VR-based pipeline synchronizing 360-degree transit videos with vehicle GNSS telemetry to address the scarcity of dynamic vehicular data.
Alireza Parchami, Artin Saberpour Abadian, Robin Connor Schramm et al.· Proceedings of the 18th Inte...· 0 citations
Students in MIT’s Concourse program delve deeply into the human condition, debate challenging questions, and learn to develop judgment about issues that can’t be quantified.
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduSep 30, 2026
Able to defeat top-ranked human players and more efficient than other models, the new system could help decision-makers in military maneuvers or business negotiations.
Computer scientist, entrepreneur, and philanthropist will collaborate with the MIT Schwarzman College of Computing to advance AI and scientific discovery.
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